DocumentCode :
2290359
Title :
Morphological pyramids for multiscale edge detection
Author :
Chen, Wei ; Acton, Scott T.
Author_Institution :
Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA
fYear :
1998
fDate :
5-7 Apr 1998
Firstpage :
137
Lastpage :
141
Abstract :
In this paper, we present an edge detector that is based on a morphological pyramid (MP) structure. The algorithm utilizes a multiresolution pyramidal structure created by successive morphological filtering and subsampling of the original image. The boundaries detected at coarse scale representations of the morphological pyramid (MP) are used to guide the detection of discontinuities at higher resolution levels. The segmentation and resulting edge detection yielded by the MP is particularly effective in the presence of impulse noise. We provide results that demonstrate superior solution quality over standard fixed resolution detectors and over previous multiresolution approaches. Because of the low computational cost of the MP edge detector, it is suitable for video tracking, image and video compression, and real-time object recognition
Keywords :
edge detection; filtering theory; image resolution; image segmentation; mathematical morphology; coarse scale representations; discontinuities detection; higher resolution levels; image compression; image segmentation; image subsampling; impulse noise; low computational cost; morphological filtering; morphological pyramids; multiresolution pyramidal structure; multiscale edge detection; real-time object recognition; video compression; video tracking; Band pass filters; Computational efficiency; Detectors; Filtering; Image edge detection; Image resolution; Image sampling; Image segmentation; Nonlinear filters; Video compression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Interpretation, 1998 IEEE Southwest Symposium on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-4876-1
Type :
conf
DOI :
10.1109/IAI.1998.666874
Filename :
666874
Link To Document :
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